Recently, the AbdomenCT-1K dataset [1]} established abdominal organs datasets by using the pre-trained model for predictions and then refining by radiologists. However, these model predictions could affect the annotator's decision, especially in boundary regions with low contrast. Different from AbdomenCT-1K [1]}, all scans in the WORD dataset are annotated from scratch manually. A senior oncologist (with seven years of experience) uses ITK-SNAP [3]} to delineate organs slice-by-slice in axial view. After that, an expert of oncology (more than 20 years experience) checks these annotations carefully. Note that, all annotations obey the radiation therapy delineation guideline published by Radiation Therapy Oncology Group (RTOG)https://www.rtog.org/. In the annotation stage, each volume roughly takes a spend of 1.2-2.6 hours to annotate all 16 organs and further requires 0.4-1.0 hours to check and refine the annotation. The WORD dataset takes us around 15 months to collect, annotate and check, so we think it's very precious and desirable to share with the whole computer vision community.
